Complex-Valued Depthwise Separable Convolutional Neural Network for Automatic Modulation Classification-Reference-Cited by-同舟云学术

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Complex-Valued Depthwise Separable Convolutional Neural Network for Automatic Modulation Classification

Published:2023 Issue: Volume:72 Page:1-10
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Xiao Chenghong¹^ORCID,Yang Shuyuan¹^ORCID,Feng Zhixi¹^ORCID

Affiliation:

1. School of Artificial Intelligence, Xidian University, Xi’an, China

Funder

National Natural Science Foundation of China

Science and Technology Innovation Team in Shaanxi Province of China

High-Performance Computing Platform of Xidian University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10012124/10198896.pdf?arnumber=10198896

Reference28 articles.

1. Convolutional radio modulation recognition networks;o’shea;Proc Int Conf Eng Appl Neural Netw,2016

2. A Radio Signal Recognition Approach Based on Complex-Valued CNN and Self-Attention Mechanism

3. Sequential Convolutional Recurrent Neural Networks for Fast Automatic Modulation Classification

4. Fast deep learning for automatic modulation classification;ramjee;arXiv 1901 05850,2019

5. Quadruplet Convolution Neural Network With C3 Loss (C3-QCNN) for Signal Classification

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1. CNN-based automatic modulation recognition for index modulation systems;Expert Systems with Applications;2024-04

2. An Efficient and Lightweight Model for Automatic Modulation Classification: A Hybrid Feature Extraction Network Combined with Attention Mechanism;Electronics;2023-08-30

3. Automatic Modulation Classification Based on CNN-Transformer Graph Neural Network;Sensors;2023-08-20

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